CBN Tool Life Prediction by Artificial Neural Network

Abstract

For economic application of CBN tools it is important to know how the tool life changes as a function of the most important technological parameters (cutting speed, feed rate, depth of cut and work piece diameter). These technological parameters have significant effects on the productivity of machining. The extended Taylor equation takes the effects of feed rate, depth of cut into account besides the cutting speed, but this equation is not valid in the whole range of cutting speed. Beyond the publicated tool life equations in the professional articles, the tool life can be determined by Artificial Neural Network (ANN). ANNs have huge flexibility and can handle different number of inputs thus they are suitable for determining tool life as a function of several cutting parameters.